Guidelines for Conducting Mixed-methods Research: An Extension and Illustration

By V. Venkatesh, Susan A. Brown, Yulia W. Sullivan. Journal of the AIS, 2016

623 citations recorded by the source corpus.

In this paper, we extend the guidelines of Venkatesh et al. (2013) for mixed-methods research by identifying and integrating variations in mixed-methods research. By considering 14 properties of mixed-methods research (e.g., purposes, research questions, epistemological assumptions), our guidelines demonstrate how researchers can flexibly identify the existing variations in mixed-methods research and proceed accordingly with a study design that suits their needs. To make the guidelines actionable for various situations and issues that researchers could encounter, we develop a decision tree to map the flow and relationship among the design strategies. We also illustrate one possible type of mixed-methods research in information systems in depth and discuss how to develop and validate metainferences as the outcomes of such a study.

Subfields: Management Information Systems

View Paper: https://www.semanticscholar.org/paper/82ece8aae00e9a1e9640f87214e82904f3b3bfdb

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1. Christoph Neuberger
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Citations in the corpus

• Social media analytics - Challenges in topic discovery, data collection, and data preparation (2018, background): “This discipline has a long history of combining the two paradigms, and researchers struggling to accomplish the same in their own research may fi nd the IS literature on the subject useful (Venkatesh, Brown, & Bala, 2013; Venkatesh, Brown, & Sullivan, 2016).”